Linking Science Data and Research ESIP.pdf (602.98 kB)
Linking Science Data and Research to Enable Data and Knowledge Discovery
posterposted on 2021-01-20, 19:39 authored by Irina Gerasimov, Andrey Savtchenko, Jerome Alfred, Jennifer Wei
NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven data discovery, where users seek publications on projects similar to their intended study. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. To create knowledge representations of science carried out in these publications, we use existing ontologies such as GCMD and SWEET. These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, realms, among many others. A database of these terms can be used to enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. This poster was presented at the 2021 Earth Science Information Partners (ESIP) Winter Meeting held virtually in January 2021.